import { calculatePromptCost, calculateCompletionCost } from "tokencost"; const messages = [ { role: "system", content: "You are a helpful assistant." }, { role: "user", content: "What is the prime directive?\n", }, ]; const promptCost = calculatePromptCost(messages, "gpt-4o");...
关于Token,虽然不同的模型有不同的计算(计费)方式,但常见的终归是这么四种:gpt2、p50k_base、p50k_edit、r50k_base、cl100k_base。 在OpenAI 官方的项目openai/tiktoken[3]中,我们能够找到官方是如何使用 Rust 来快速计算文本包含 Token 数量的。不过,如果你想了解具体哪些模型用上述的具体算法来进行计算,我更...
根据OpenAI GPT-3模型每10,000个tokens消耗12美元的价格,这个对话的成本大约为0.05美元或约合0.34元...
After a recentprice reductionby OpenAI, GPT-4o tokens now cost $4 per million tokens (using a blended rate that assumes 80% input and 20% output tokens). GPT-4 cost $36 per million tokens at its initial release in March 2023. This price reduction over 17 months corresponds to about a...
const tools = [new TavilySearchResults({ maxResults: 1, apiKey: 'MY-API-KEY' })]; const llm = new ChatOpenAI({ modelName: "gpt-4-turbo", temperature: 0.15, maxRetries: 3, timeout: 30000, callbacks: [ { handleLLMEnd(output) { console.log(output) output.generations.map(generation...
所以新闻中那个成本比较不科学,实际token/cost还可以做到更高。另外,这个架构潜力在于,4nm的SRAM密度比...
Evaluating the number of tokens in your input is important because it helps you understand the cost of your request and the limitations of the model. By evaluating the number of tokens it takes for your request, you can determine the following: ...
1. Enter the number of words in your prompt to GPT 2. Hit that beautiful Calculate button 🎉 3. Get your estimated token count based on your words Calculate Estimated Tokens This is a simple calculator created to help you estimate the number of tokens based on the known number of words...
数值“380”在 GPT 中标记为单个“380”token。但是“381”表示为两个token[“38”,“1”]。“382”同样是两个token,但“383”是单个token[“383”]。一些四位数字的token有: [“3000”] ,[“3”,“100”] ,[“35”,“00”] ,[“4”,“500”]。这或许就是为什么基于 GPT 的模型并不总是擅长...
However, please note that the cost for GPT-4 models are significantly higher than GPT-3.5 models so please also take that into consideration. Use prompt patterns. One possible solution would be make use of Map-Reduce kind of pattern where you chunk your data in smaller pieces and send each...